Generally speaking, optical character recognition (OCR) attempts to decode symbols using image-processing techniques. Typically, such an approach is time-consuming, as it involves moving outline templates around, and performing calculations for each position. A high-speed method capable of efficient optical character recognition is needed.
Several attempts have been made to improve optical character recognition. For example, U.S. Pat. No. 5,317,652 by Chatterjee discloses a character recognition system implementing concurrent processing and vector correlation. Specifically, a character image in a buffer is vector-correlated with character templates represented as discrete character skeletons comprised of dots. Although the reference discloses comparison of dots around a centerline template, it does not mention assigning template scores based on the number of dots inside or outside the printed character. U.S. Pat. No. 7,724,958 by Walch discloses a biometric handwriting identification system for converting characters and a writing sample into mathematical graphs, followed by using optical character recognition to identify features in the handwriting sample. The reference mentions using OCR to compare centerlines of stored and current images. However, to score a character match the template is superimposed over the actual image, and pixels of the actual image are then analyzed. The method does not use an analysis of a limited set of points to score a character match. U.S. Pat. No. 6,628,808 by Bach et al. discloses a method of verifying a scanned image using a topological analysis. To score a character match at a given candidate location, a template is superimposed over an actual image, and pixels on the actual image falling beneath the centerline pixels on the template are analyzed. Similar to U.S. Pat. No. 7,724,958, the method relies on pixel analysis, and does not mention centerline analysis conducted with a limited set of points, and may therefore be rather time-consuming.
Therefore, a need exists for a quick and efficient template-matching method having OCR decoding time comparable to barcode scanning time.